diff --git a/tripy/tripy/frontend/ops/outer.py b/tripy/tripy/frontend/ops/outer.py
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+++ b/tripy/tripy/frontend/ops/outer.py
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+#
+# SPDX-FileCopyrightText: Copyright (c) 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+from tripy import export, constraints
+import tripy.frontend.utils as frontend_utils
+
+
+@export.public_api(document_under="operations/functions")
+@frontend_utils.convert_inputs_to_tensors(sync_arg_types=[("vec1", "vec2")])
+@constraints.dtype_info(
+    dtype_variables={"T1": ["float32", "float16", "bfloat16", "float8", "int4", "int8", "int32", "int64", "bool"]},
+    dtype_constraints={"vec1": "T1", "vec2": "T1", "other": "T1", constraints.RETURN_VALUE: "T1"},
+)
+def outer(vec1: "tripy.Tensor", vec2: "tripy.Tensor") -> "tripy.Tensor":
+    r"""
+    Computes the outer product of 1-d vectors `vec1` and `vec2`, such that the
+    output dimension is (m x n) if the inputs are of size m and n respectively.
+
+    Args:
+        vec1: The first 1d input vector.
+        vec2: The second 1d input vector
+
+    Returns:
+        The outer product of the input vectors.
+
+    .. code-block:: python
+        :linenos:
+        :caption: Example
+
+        v1 = tp.arange(5, dtype=tp.float32)
+        v2 = tp.arange(4, dtype=tp.float32)
+        output = tp.outer(v1, v2)
+
+        t1 = torch.arange(5, dtype=torch.float32) # doc: omit
+        t2 = torch.arange(4, dtype=torch.float32) # doc: omit
+        assert tp.allclose(output, tp.Tensor(torch.outer(t1, t2)))
+    """
+    from tripy.frontend.trace.ops.unsqueeze import unsqueeze
+
+    return unsqueeze(vec1, -1) * unsqueeze(vec2, 0)
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